To overcome the short-comings of current multi-spectral PFT products (supplying either knowledge on dominant groups or size fractions only, data products with strong linkage to a-priori-information) and PhytoDOAS data products (with only low temporal and spatial coverage), the project's objective is a substantial improvement of retrieving phytoplankton groups with defined accuracy and good spatial and temporal coverage. This shall be done by developing a synergistic product which contains the Chl-a (biomass) of several PFT by using complementary information from multi- and hyper-spectral satellite ocean colour data. This algorithm can be later applied to produce a synergistic PFT product from TROPOMI (on Sentinel-5-Precursor, Sentinel-4, Sentinel-5) and OLCI (on Sentinel-3).

The synergistic PFT algorithm was conceived to generate global PFT Chla products of diatoms, coccolithophores and cyanobacteria (Losa et al. in prep) from 2002 to 2012 at daily 4 km resolution. The algorithm is based on an optimal interpolation technique (Gandin and Hardin 1965) and applied for combining improved products of OC-PFT and PhytoDOAS, with PhytoDOAS giving the physical value within the large pixel and OC-PFT giving the sub- pixel variation by given a certain weight to each of these inputs. The weights are defined in terms of Kalman filtering, reflecting the error statistics in both products. The algorithm can be run on open source software and the product outputs are provided as NetCDF. The algorithm inputs are available in ASCII or NetCDF.

SynSenPFT output was successfully validated with in-situ PFT data sets and intercompared to the same outputs from the NASA ocean biogeochemical model (NOBM, Gregg and Casey 2007) and two similar satellite data sets (Ciotti et al 2006, Brewin et al. 2010, respectively) describing the composition of phytoplankton in terms of size. Validation against in-situ data showed globally robust results for all three SynSenPFT products (Losa et al. 2012): SynSenPFT Chla show good comparison (among all statistical parameters) to in-situ PFT for coccolithophores and diatoms. For cyanobacteria RMSD and MAE are still acceptable, however no correlation was found. Inter-comparison of other global satellite products and to NOBM products at monthly resolution shows reasonable similar spatial and temporal distribution and magnitudes for all three SynSenPFT products (Losa et al. in prep.). Additional the inter-comparison analyses, including calculations of correlations, trends and bloom phenology, was carried out through time series analyses for specific Longhurst provinces encompassing polar, oligotrophic, tropical and upwelling regions, (Soppa et al. in prep.). Generally, SynSenPFT products are similar to the corresponding c-PSC and, for some provinces, to NOBM Chla (especially for diatoms). Differences in the magnitude depend on the PFT and region. Only a few significant trends were detected and these were consistent for c-PSC and SynSenPFT for Canarian Coastal and the Southwest Atlantic Shelf provinces. The phenological indices of c-PSC and NOBM Chla were consistent within two to three months, respectively to SynSenPFT products. PSC products indicated longer bloom duration, which may be explained by these products covering more algal groups than the ones detected by SynSenPFT. In summary, the first version of SynSenPFT shows robust results based on its uncertainty determined via validation and intercomparison to other products.

All the data sets compiled and used in the frame of this project are available on request and all the project documents (deliverables, technical notes), the SynSenPFT presentations and publications, are accessible via the project website.